In this repository, you can find resources to replicate the analysis of IllustrisTNG data presented in Pathak et al. (2021).
We also provide some resources for streamlining your analysis of relevant IllustrisTNG data with detailed instructions to download and process this data.
We include two additional figures to complement the results presented in Pathak et al. (2020), and to facilitate further discussion. Scroll to the bottom of Figures.ipynb and look under Extras to view the new figures.
For a quick view, we include compiled and rendered .HTML previews of both Jupyter Notebooks in preview_analysis that only require a working browser to open and browse.
All data acquisition and analysis in this project was done in Python 3.8.3.
We suggest downloading all notebooks, modules, and data files included in this repository before starting your analysis.
Follow the steps outlined in the notebook. If this is your first time working with IllustrisTNG data, do not skip Step 0. Go to www.tng-project.org to set up an account and get an API key. Detailed steps are included in the notebook. You will need this API key to download TNG data from the server.
Note that downloading data on individual galaxies from the TNG server requires a stable internet connection. Most of the subsequent analysis can be done offline.
This notebook also provides instructions for storing data on individual galaxies, calculating halo properties from downloaded data, and compiling data on selected populations.
This notebook analyzes the data that was downloaded and processed in Data_Acquisition.ipynb.
This notebook will help you generate all five figures from Pathak et al. (2021).
This repository does not host any proprietary data. All data included in this repository has been processed before release. Appropriate citations for the original data (not included in repository) have been included below.
Some post-processed data from the IllustrisTNG public data release have been included.
Details can be found at: (Nelson et al. 2019a); Pillepich et al. (2018b); Springel et al. (2018); Nelson et al. (2018a); Naiman et al. (2018); Marinacci et al. (2018).
A huge thank you to Wren Suess for sharing her data!
Some data from Suess et al. (2020) was processed similar to our halo selection function, and population percentiles have been included in Suess2020_data.hdf5 for reproducing the comparisons with observations in Figure 2.
Calculations for halo data in the the field maximum_merger_ratio_30kpc_current_fraction in galaxy_population_data_2.hdf5 was done by post-processing data from Stellar Assembly Files provided by Vicente Rodriguez-Gomez. Details can be found at Rodriguez-Gomez et al. (2016).
If you have any questions or comments, please reach out to [email protected]!